TY - JOUR
T1 - Invariant distribution of promoter activities in Escherichia coli
AU - Zaslaver, Alon
AU - Kaplan, Shai
AU - Bren, Anat
AU - Jinich, Adrian
AU - Mayo, Avi
AU - Dekel, Erez
AU - Alon, Uri
AU - Itzkovitz, Shalev
PY - 2009/10
Y1 - 2009/10
N2 - Cells need to allocate their limited resources to express a wide range of genes. To understand how Escherichia coli partitions its transcriptional resources between its different promoters, we employ a robotic assay using a comprehensive reporter strain library for E. coli to measure promoter activity on a genomic scale at high-temporal resolution and accuracy. This allows continuous tracking of promoter activity as cells change their growth rate from exponential to stationary phase in different media. We find a heavy-tailed distribution of promoter activities, with promoter activities spanning several orders of magnitude. While the shape of the distribution is almost completely independent of the growth conditions, the identity of the promoters expressed at different levels does depend on them. Translation machinery genes, however, keep the same relative expression levels in the distribution across conditions, and their fractional promoter activity tracks growth rate tightly. We present a simple optimization model for resource allocation which suggests that the observed invariant distributions might maximize growth rate. These invariant features of the distribution of promoter activities may suggest design constraints that shape the allocation of transcriptional resources.
AB - Cells need to allocate their limited resources to express a wide range of genes. To understand how Escherichia coli partitions its transcriptional resources between its different promoters, we employ a robotic assay using a comprehensive reporter strain library for E. coli to measure promoter activity on a genomic scale at high-temporal resolution and accuracy. This allows continuous tracking of promoter activity as cells change their growth rate from exponential to stationary phase in different media. We find a heavy-tailed distribution of promoter activities, with promoter activities spanning several orders of magnitude. While the shape of the distribution is almost completely independent of the growth conditions, the identity of the promoters expressed at different levels does depend on them. Translation machinery genes, however, keep the same relative expression levels in the distribution across conditions, and their fractional promoter activity tracks growth rate tightly. We present a simple optimization model for resource allocation which suggests that the observed invariant distributions might maximize growth rate. These invariant features of the distribution of promoter activities may suggest design constraints that shape the allocation of transcriptional resources.
UR - http://www.scopus.com/inward/record.url?scp=73449149110&partnerID=8YFLogxK
U2 - 10.1371/journal.pcbi.1000545
DO - 10.1371/journal.pcbi.1000545
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C2 - 19851443
AN - SCOPUS:73449149110
SN - 1553-734X
VL - 5
JO - PLoS Computational Biology
JF - PLoS Computational Biology
IS - 10
M1 - e1000545
ER -